Institute for Communication Technologies
www.itc.com.unisi.ch
Faculty of Communication Sciences
Università della Svizzera italiana
via Buffi 13 CH-6900 Lugano
Artificial Institutions: A Model of Institutional Reality for Open Multiagent Systems Nicoletta Fornara, Francesco Viganò, Mario Verdicchio, and Marco Colombetti
Institute for Communication Technologies
Università della Svizzera Italiana, 2006.
Reality for Open Multiagent Systems
?Nicoletta Fornara1, Francesco Vigan`o1, Mario Verdicchio2, and Macro Colombetti1,3
1 Universit`a della Svizzera italiana, via G. Buffi 13, 6900 Lugano, Switzerland {nicoletta.fornara, francesco.vigano, marco.colombetti}@lu.unisi.ch,
2 Universit`a degli Studi di Bergamo, via Salvecchio 19, 24100 Bergamo, Italy [email protected]
3 Politecnico di Milano, piazza Leonardo Da Vinci 32, Milano, Italy [email protected]
Abstract. Software agents’ ability to interact within different open sys- tems, designed by different groups, presupposes an agreement on an un- ambiguous definition of a set of concepts, used to describe the context of the interaction and the communication language the agents can use.
Agents’ interactions ought to allow for reliable expectations on the possi- ble evolution of the system; however, in open systems interacting agents may not conform to predefined specifications. A possible solution is to define interaction environments including a normative component, with suitable rules to regulate the behaviour of agents.
To tackle this problem, we propose an application-independent model of artificial institutions that can be used to define open multiagent systems.
With respect to other approaches to artificial (or electronic) institutions, which mainly focus on the definition of the normative component of open systems, our proposal has a wider scope, in that we model the social con- text of the interaction, define the semantics of an Agent Communication Language to operate on such a context, and give an operational defini- tion of the norms that are necessary to constrain the agents’ actions. In particular, we define the semantics of a library of communicative acts in terms of operations on agents’ social reality, more specifically on com- mitments, and regard norms as event-driven rules that, when fired by events happening in the system, create or modify a set of commitments.
An interesting aspect of our proposal is that both the definition of the ACL and the definition of norms are based on the same notion of com- mitment. Therefore an agent capable of reasoning on commitments can reason both on the semantics of communicative acts and on the norma- tive system.
1 Introduction
Since the advent of the Internet, about ten years ago, the landscape of computer science has substantially changed. For the first time, it has become feasible to
?Supported by Swiss National Science Foundation project 200021-100260, ”An Open Interaction Framework for Communicative Agents”
develop open distributed systems, that is, software systems whose components can aggregate dynamically and are free to enter and leave an interaction at their will. In an open distributed system, the interacting agents are typically designed and implemented by different parties, and may represent conflicting interests, as it happens for example in e-commerce applications. This fact has two important consequences. The first is that interaction will not even be possible unless agents are designed to comply with well-defined standards. The second consequence is that interaction will not lead to coherent outcomes unless the agents’ behaviour is suitably regulated. The first problem (i.e., the problem of standards) has been tackled by a number of organizations, including FIPA, the Foundation for Intelligent Physical Agents (http://www.fipa.org). The second problem (i.e., the problem of regulating interactions) is much more elusive, and has become an important object of research at least since Noriega’s and Sierra’s works on electronic institutions in the late nineteen-nineties [21, 20]. Since then, several authors (see for example [10, 1, 30, 31, 11, 3]) have contributed to the specification of electronic institutions and artificial institutions [14, 34].
An electronic institution is usually viewed as a set of norms, which the agents interacting within an open distributed systems ought to follow [20]. Interaction protocols themselves can be conceived as sets of norms (about what an agent may do and when), and are the most obvious component of an electronic insti- tution [11]. As a whole, the function of an electronic institution is to guarantee that if its norms are followed by all agents, the interaction will produce a de- sirable outcome. Indeed, it is part of the very concept of an autonomous agent that norms may be violated; the system implementing an electronic institution ought to detect such violations and to manage the situation, for example by applying suitable sanctions. Given that norms are an essential component of social reality (see for example [25]), we can regard electronic institution as a means for imposing a well-defined structure to the social reality within which agents interact. However, norms are just one component of social reality; other components, which also seem to us to be important for the specification of open distributed systems, have been largely neglected by most proposals concerning electronic institutions. For this reason we would like to put forward an extension of the concept of an electronic institution, that we call “artificial institution”.
Social reality is that part of the world that exists only because it is collec- tively recognized to exist by a group of agents. Norms are an obvious example of something that exists only because it is accepted by the members of some com- munity; other important components are: (i) a socially defined ontology, and (ii), linguistic conventions. Let us briefly analyse these components.
Institutions not only regulate, but also create components of social reality.
For example, the institution of ownership does not just regulate a pre-existing piece of reality, but creates the very concept of owning something. In other words, an institution introduces a new ontology, including a set of entities with their properties and relationships. A very important class of entities created by an institution is the set of institutional actions. For example, actions like
selling and buying, renting and hiring, lending and borrowing (and, in fact, also stealing) are only meaningful within a suitable institution of ownership.
Contrary to natural actions, like eating or walking around, institutional ac- tions cannot be executed only by exploiting physical abilities. Rather, they re- quire suitable conventions that allow agents to perform institutional actions by producing certain forms of behaviour, typically linguistic behaviour. The need of specifying linguistic conventions for open distributed systems has been recog- nised at least since the definition of KQLM [12]. Since then, Agent Commu- nication Languages (ACLs) have been an important subject of research. Early models of multiagent systems tended to regard ACLs as local to every specific system (or even to every pair of roles in the system, as suggested by the Aalaadin model [17]). Later research in agent communication, however, highlighted the im- portance of defining a universal ACL [7, 29]. Moreover, some approaches to the semantics of ACLs show that the very definition of a communication language may be based on elements of social reality, like the concept of commitment [28, 4, 5, 14]: if this approach is correct, ACL messages can be understood only within a suitable system of artificial institutions.
In general, producing an instance of the correct conventional behaviour is necessary but not sufficient to perform an institutional action. For example, the president of society can open the annual meeting by saying “The meeting is open”, while a generic member of the society cannot do the same. The issue, here, is power or, as we prefer to call it, authorization: institutional actions are successful only if they are performed by an authorized agent, and authorizations are typically associated to the roles played by the agent in the institution. Even authorized actions, however, cannot always be performed freely. For example, the owner of a car is authorized to sell it, but may be prohibited to do so by his or her spouse (in this example two institutions, ownership and family, interact).
In an institution, a set of norms typically regulate the execution of authorized action.
This brief analysis shows that institutions are made up by a number of com- ponents: an ontology (including the definition of institutional actions), a set of authorizations to perform institutional actions (typically associated to roles), a set of linguistic conventions for the execution of institutional actions, and a system of norms regulating the agents’ interaction. All these components are so strictly interconnected that they have to be dealt with within a single concep- tual framework. The metamodel of artificial institutions that we propose in this paper is an attempt to define such a framework. Our presentation is structured as follows. In Section 2 we introduce our metamodel of artificial institutions, defining their fundamental concepts and relationships. In Section 3 an example of the specification of an artificial institution, the Basic Institution, is presented.
Using the notion of commitment defined by the Basic Institution, in Section 4 we present our operational definition of norms. Finally, in Section 5 we conclude with a brief discussion of related work and open questions.
2 A Metamodel of Artificial Institutions
Artificial institutions aremodels of institutional reality which specify a class of interaction domains by exploiting a set of common concepts and notations. For this reason we introduce a metamodel of artificial institutions to describe an abstract syntax and a semantics for each construct that characterizes artificial institutions. In Figure 1 the abstract syntax is presented by means of a notation inspired by the UML metamodel [23], showing the fundamental concepts and the relationships existing between them.
Even if we have adopted a notation inspired by UML, we are not prescribing that artificial institutions and agents acting within them should be implemented by object oriented technologies. In fact, artificial institutions are intended to specify institutional reality for open multiagent systems, which are characterized by the fact that heterogeneous agents realized with different technologies and by different organizations should interact. Therefore, it is important that the specification does not commit to a specific implementation language, platform, or internal architecture. For this reason, we do not exploit most of the features of object oriented technologies, like methods or polymorphism, and to avoid confusion we will not talk of classes. Therefore, we do not adopt the meta- metamodel of UML4, which introduces, among others, the concept of MetaClass and MetaOperations.
We use UML as a starting point, reusing its well known graphical notation and the Object Constraint Language (OCL [22]) as our language to express constraints. An advantage of this approach is that it employs concepts that are close to the intuition and knowledge of practitioners. We believe the metamodel we have developed can be easily understood by software engineers who design and implement open multiagent systems.
Like the metamodel of UML, our metamodel of artificial institution has a declarative semantics and suppresses implementation details. Therefore, we ab- stract away from methods and implementation issues and provide an abstract syntax to specify agent interaction systems.
In this paper we do not propose a specific architecture for the management of institutional states in real systems, because we think that different architectures may be chosen and adapted according to the needs of real systems. Anyway, agents using the interfaces specified through an artificial institution model should not even notice the existence of such design and implementation choices.
In the following sections we shall introduce a notation for the components of artificial institutions and describe their meaning in natural language, whereas the metamodel reported in Figure 1 provides a set of well-formedness rules for a model of an artificial institution. In Section 3 we will exemplify our approach by defining a model of a specific institution, the Basic Institution.
2.1 The Core Ontology
4 For reason of conciseness we do not discuss our meta-metamodel and the relations existing between it and the meta-metamodel defined by UML.
Relationship
Association Role Agent
Entity target
source
source
InstitutionalAction Attribute
InstitutionalAttribute NaturalAttribute
AssociationEntity
Authorization authorized
toPerform
OCLExpression condition
Event EventAttribute
Parameter ECA
EventTemplate
on do
OCLExpression if
Action
ExchMessage
TemplateAttribute 1
*
*
*
*
1 1
1 1
1
1
1 1 1
1..*
1 1..*
*
*
*
*
*
1..*
*
*
* *
*
Fig. 1.The artificial institution metamodel.
Entities In our view, artificial institutions are a technological extension of hu- man reality and therefore they should represent part of thestateof the real world.
We assume the existence ofexternal ontologies defining classes of entities, their relationships and the relevant attributes representing physical properties. For example, an entity may represent a book, which may have a number of pages and a weight. We represent entities, attributes and relations with UML class diagrams.
Thecore ontologyis introduced to define new features relative to such entities which exist only thanks to agents’ common agreement. For instance, the price of a product on sale exists only because a community of agents recognizes such a property.
For this reason we distinguish between two types of attributes that can be associated to the definition of entities:natural attributes, which represent physi- cal properties and are defined by external ontologies, andinstitutional attributes, which reflect the existence of a common agreement and are introduced by core ontologies.
Sometimes, core ontologies define entities whose attributes are only institu- tional, like thecommitment entitydefined by the Basic Institution described in Section 3. We refer to such entities as institutional entities.
Institutional Actions In our framework we assume that agents can mod- ify only institutional attributes by performing a particular set of actions, that is, institutional actions [6]. An institutional action describes how institutional attributes change as a consequence of its performance. For example, in [14]
communicative acts are regarded as institutional actions, because they create commitments or modify their attributes.
More precisely, an institutional action is characterized by:
– anaction name;
– a possibly empty set ofparameters;
– a possibly empty set ofontological preconditions, which specify the values that certain institutional attributes must have for the action to be meaningful (for example, opening an auction is meaningful only if the auction is not already open);
– a nonempty set ofpostconditions, which specify the values of certain insti- tutional attributes after a successful performance of the action.
Preconditions and postconditions of institutional actions are expressed through OCLExpressions [22], which can refer only to the parameters of the institutional action or institutional attributes defined by the core ontology, reflecting the fact that the only effect of an institutional action is to modify institutional attributes.
Because institutional actions change institutional attributes, which exist only thanks to common agreement, it follows that institutional actions have an intrin- sic social nature. Therefore, agents cannot perform such actions by exploiting causal links occurring in the natural world, as it would be done to open a door or to move a physical object. Furthermore, a crucial condition for the actual perfor- mance of institutional actions is that they must bepublic, that is, made known to the relevant agents by means of some action that can be directly executed by an artificial agent. In the human world such instrumental actions vary from certain bodily movements (raising one’s arm to vote), to the use of specific phys- ical tools (waving a white flag to surrender), to the use of language (saying “the auction is open” to open an auction). We assume that in a multiagent system all institutional actions are performed by means of a single type of instrumental action, namely exchanging a message.
Roles A core ontology also defines a set of relationships between agents and entities, and we regard such relationships asroles; thus roles are always defined relative to entities. For example, an agent can be the owner of a commodity.
Clearly, such relationships are supported by the common agreement of agents and therefore roles have the same nature and characteristics of institutional attributes. Therefore, roles are also institutional facts and they can be changed only by performing institutional actions.
As the metamodel reported in Figure 1 shows, a role is related to authoriza- tions and Event-Condition-Action rules (ECA rules, see Section 2.3) which are also used to represent norms (see Section 4). Therefore, roles can also be seen as way to relate agents to their authorizations and norms, abstracting from the concrete agents that will be actually involved in an interaction. In general, a sound specification of an artificial institution cannot define a role with an empty set of authorizations or ECA rules.
Events A core ontology also describes a set of events which are relevant for the definition and activation of ECA rules (see Section 2.3). UML models four kinds of events [23] :signals,calls,passing of time andchange in state. Unfortunately, the notation proposed in UML for modeling events is bound to features of State Machine and Statechart Diagrams, while we need a way to describe events in general.
In our framework, an event type can have attributes, providing information about the state transition that caused it, and it is possible to model hierarchies of event types. Moreover we assume that every event has atimeattribute reporting the time at which an event has occurred. In our formalization we have singled out three main categories of events:
– a TimeEvent, which occurs when the system reaches a certain instant of time;
– aChangeEvent, which happens when an institutional entity changes in some way. This kind of event type can be further specialized:
• anAttributeChange, which is registered when an attribute has changed its value.
• a RelationChange, which happens when a new relation iscreated or an existing one between two institutional entities isdropped.
• a GeneralizationChange, which occurs when an entity modifies its type in a given taxonomy.
– anActionEvent, that happens when an agent perform an action. In partic- ular, an interesting type of this kind of events isExchMsg, which represents the act of exchanging a message.
The definition of event types allows us to define event templates, that is, event types that have some restriction on certain attributes and describe a set of possible event occurrences. Event templates are used in the on section of ECA rules to specify what kind of domain dependent events activates a rule.
2.2 Authorizations and Conventions
Given that institutional actions modify institutional attributes, agents cannot directly perform such actions. Instead, we assume that all institutional actions are performed by exchanging messages, thanks to constitutive rules [25] which bind the exchange of a message to the performance of an institutional action.
To model the connection between instrumental actions and institutional ac- tions we introduce the notion of aconvention, that is, an agreement about what type of message is bound to a given type of institutional action. In our model the definition of a convention has the following generic form:
ExchM sg(message type, sender, receivers,iaction(parameters)) =conv
iaction(parameters)
In [14] we have defined some useful conventions for the performance of insti- tutional actions (in particular communicative acts). For example, by definition
[24], the content of a declaration describes precisely the institutional changes that it brings about. Therefore, we take messages of type declare as the funda- mental means to perform institutional actions and the convention is defined as follows:
ExchM sg(declare, sender, receivers, content) =conv
iaction(parameters)
By itself, a convention is not sufficient to guarantee the successful perfor- mance of an institutional action by the exchange of the appropriate message:
indeed, some additionalcontextual conditions2must be satisfied about the agent that sends the message, about the agents that receive the message, and about the state of the system in relation to the content of the message.
Conditions on the sender of the message. The sender of the message must be authorized to perform an institutional action. In the specification of an in- teraction system authorizations are expressed in term of roles; for example, only the auctioneer can open an auction by sending a suitable message to the partic- ipants. Moreover an authorization can be given only if certain conditions about the state of the system, expressed by suitable Boolean expressions, are satisfied.
For example, it may be established that an auction is validly opened only if there are at least two participants. Therefore, we abstractly define the authorization to perform a specific institutional action (with given parameters) associating it to a role defined in the context of a specific entity as follows:
Auth(entity.role, iaction(param), conditions)
It is worth highlighting that authorizations are a necessary condition for the successful performance of an institutional action and that designers should spec- ify a set of authorizations whenever they introduce a new institutional action.
As we will see in Section 4, this fact allows us to assume that everyauthorized institutional actions that is not prohibited ispermitted.
Conditions about the receivers of the message. Secondly, messages realizing institutional actions should be received by all agents that are affected by the performance of the act; for example all the participants of an auction must re- ceive the message that opens it.
Conditions about the state of the system.All the preconditions of the institu- tional action associated to the performance of the exchange of the message must be satisfied; for instance, an auction cannot be closed if it has not been opened yet.
2 Following Searle [25], the construction of social reality in the human world is pos- sible thanks to constitutive rules of the form X counts as Y in C. Similarly, in an artificial system constitutive rules bind the performance of a message exchange to the corresponding institutional action only if certain conditions about the context are satisfied.
2.3 Event-Condition-Action Rules
The last component of our metamodel is represented by Event-Condition-Action rules, which allow us to model the fact that institutional reality may change as a consequence of the occurrence of certain events. For example, a competition may start at a fixed time instant and be considered closed at another time without an agent having declared it. ECA rules are also useful to model how the performance an institutional action executed within an institution may affect another institution (see for example [34]).
Inspired by Active Database models, we define an ECA rule as composed by three elements:
1. an event template, which represents the class of events which may activate the rule.
2. a condition, expressed through a Boolean OCLExpression, which can refer to the variableewhich contains a description of the event that has activated the rule.
3. a nonempty set ofinstitutional actions which are executed by the rules.
The semantics of ECA rules is given as usual: when an event matching the description given by the event template occurs in the system, the variablee is filled with the event instance and the condition is evaluated; if the condition is verified, the set of institutional actions are executed and their effects are brought about in the system. We assume that the system is authorized by default to perform every institutional action. In our model, ECA rules are specified according to the following notation:
one:event-template if conditionthen
doinstitutionalAction(parameters)+
As we will see in Section 4, we define norms as ECA rules that perform institutional actions creating, canceling or modifying commitments. Therefore, before introducing norms, we need to define the Basic Institutions, that is, the artificial institution that defines what social commitments are.
3 The Basic Institution
The Basic Institution is the institution that defines a fundamental concept:
the notion of social commitment. The importance of commitment is due to the fact that, from our perspective, it is essential to express the meaning of most types of communicative acts (see [13, 14]) and because it is used to define the semantics of norms as will be shown in Section 4. Therefore we assume that the Basic Institution has to be used, together with other special institutions, in the specification of every open interaction framework.
In this section we report a fragment of the specification of an artificial insti- tution, the Basic Institution, using the concepts and the meta-model introduced
so far (for the complete specification see [14]). Other institutions, that we call special institutions, can then be defined to model the aspects of institutional reality typical of certain application domains. For instance, for electronic com- merce applications it will be necessary to model the institutions of ownership, money, business transactions, auctions, and so on. A detailed specification of the English auction, of the Dutch Auction, and of the Auction House as special institutions can be found in [14, 34].
The Basic Institution defines the ontology of commitment, the institutional actions necessary to operate on it, and a set of authorizations for the performance of these institutional actions. In general, institutions also define sets of norms to regulate the behaviour of agents, but in our current view, the Basic Institution does not specify norms.
3.1 Commitments and Temporal Propositions
In this paper we give only a short description of our model ofcommitment and oftemporal proposition, that are used to represent the content of commitments (a complete treatment of these two concepts can be found in [14, 5]). A commit- ment is characterized by the following attributes: adebtor, acreditor, acontent, and a state. Figure 2 represents the class diagram of the ontology of the Ba- sic Institution. In the rest of the paper we will refer to commitments using the following notation:
Comm(state, debtor, creditor, content)
state Commitment Agent
debtor
creditor
statement timeInterval mode truth-value
TemporalProposition content
*
*
1 1..*
1
1
Fig. 2.Class diagram of the ontology of the Basic Institution
The content of commitments is expressed using temporal propositions. A temporal proposition is characterized by astatement about a state of affairs or about an action. The statement is referred to atime interval with two possible differentmodes:exist (∃) orfor all(∀). Thetruth-valueof a temporal proposition is initiallyundefined (⊥). It becomestrue, thanks to a “notifier”, if the mode is for all and the statement is true for every instant of the associated time interval or if the mode isexistand the statement is true for some instant in the associated time interval, otherwise it becomesf alse. Temporal propositions are represented with the following notation:
T P(statement,[tstart, tend], mode, truth-value)
A commitment undergoes the life cycle described in [13] by reacting either to institutional actions performed by agents or to domain-dependent events, which modify the truth value of the temporal proposition in its content. If its temporal proposition becomes true, the commitment becomesfulfilled; if it becomes false the commitment becomesviolated. For instance the commitment of agenta1 to agent a2 to open the auction i within 10 minutes from now (or between now andnow+ 10) is represented as:
Comm(pending, a1, a2, T P(open(a1, auctioni),[now, now+10m],∃,⊥))
In our framework every agent is authorized to create a commitment by performing the makeCommitment institutional action, whose successful perfor- mance creates anunset commitment. The debtor of anunset commitment may refuse it by executingsetCancel, or it may undertake the proposed commitment by executing setPending. We represent a refused commitment by means of the cancelled state, whereas an accepted commitment is depicted with the pend- ing state. The creditor of a pending or unset commitment can always set it to cancelled. Here, due to space limitation, we report only the definition of one institutional action and of one authorization. The institutional actionmakePend- ingComm, used in Section 4, creates a pending commitment and its execution coincides with the sequential performance ofmakeCommitment andsetPending:
name:makePendingComm(debtor, creditor, content) pre: not Comm.allInstances()→exists(c|c.debtor=debtor
and c.creditor=creditor and c.content=content) post: Comm.allInstances()→exists(c|c.state=pending and
c.debtor=debtor and c.creditor=creditor and c.content=content)
Every registered agentRegAgtis authorized to create a commitment having itself asdebtor:
Auth(RegAgt,makePendingComm(debtor, creditor, content), RegAgt=debtor).
4 Norms
In the literature, it is possible to find two different approaches to the specifica- tion of norms for open systems. The more formal approach uses deontic logic to express the semantics of norms and is more suitable when the goal is to verify the consistency of a set of norms [8]. The other approach focuses on the operational aspects of norms, and is more suitable when the goal is the actual implementa- tion of norms in open systems [32, 16]. In this paper we study the formalization of norms from theinstitutional and operational perspective(opposite to the agent
perspective) [32], that is, our goal is to define norms that make the evolution of the state of an interaction system partially predictable without violating the autonomy of the interacting agents. In order to reach this purpose, norms de- scribe, on the basis of the state of the system, the expected behaviour of the agents playing different roles, and make it possible to detect deviations from such a behaviour, that is, the violation of obligations and prohibitions defined in the system.
As already said in Section 2.3 in our model norms are a special type of ECA rules characterized by the fact that when they are fired by events happening in the system, they create or cancel commitments to perform or to not perform an action within a certain interval of time, thus affectingeach agent that satisfies a suitable selection expression. Usually the collection of liable agents corresponds to the set of agents that play a given role in the institution.
From our point of view, commitments are not a specialization of norms as in [19] and norms are not themselves a special kind of commitments as in [2] and [27]. We perceive norms as rules that manipulate commitments of the agents en- gaged in an interaction. This because in the abstract formalization of a system it is important to model norms associated to roles rather than to individual agents, whereas during the actual evolution of the system it is fundamental to create commitments associated to individual agents and to detect their fulfillment or violation. Obviously such violations can be interpreted also as the violation of the corresponding norm.
When an agent fills a role in an institution, we assume that it accepts that norms will create commitments binding it to a pseudoagent representing the institution, which we call institutional agent. Such an agent allows us to keep trace of the commitments created by an instance of an institution. This also means that commitments created by norms of an institution can be cancelled only by other norms defined by the same institution, because only the creditor of a pending commitment is authorized to set it to cancelled [14]. The general structure of a norm can be described as follows:
one:event-template if conditionthen
foreachagentin selection-expression docommitment-Ops
where agent is an identifier varying on the set of agents that satisfie the selection expression; selection-expression is a list of agent identifiers or a role defined in a certain artificial institution; commitment-operationsis a sequence of commitment operations defined using BNF notation as follows:
commitment-Ops:=comm-Op |comm-Op, commitment-Ops comm-Op:=makeP endComm(agent, instAgent, content)|
cancelComm(agent, instAgent, content) content:=T P(action,[t, t],∃)|T P(¬action,[t, t],∃)
t:=now|event.time|instant|now+number|event.time+number
whereactionis an institutional action as described in Section 2;nowis the time of the system when the temporal proposition is created andinstantis an instant of time.
In [14] we give a formalization of the English Auction Institution. Here we report only an example of a norm that creates an obligation for the auctioneer to open the auction when thestart time has elapsed, if at least two agents have been registered as participants:
one:T imeEvent(a.startT ime)
if U nsetEnglishAuction.participant.sizeOf()>= 2then foreachagentinU nsetEnglishAuction.auctioneer
domakeP endingComm(agent, institutionalAgent,
T P(openAuction(U nsetEnglishAuction.id),[now, now+δ],∃))
whereδ is the time allowed to the agent to fulfill its obligation.
4.1 Normative Positions
Using our metamodel of artificial institutions and the definition of norms it is possible to represent fundamental normative positions between agents [26]:
– First of all, an institutional action has to be authorized, that is, it has to be accepted by the agents taking part to the interaction (or their designers) that the exchange of a message counts as the performance of an institutional action. If an agent performs an instrumental action bound by a convention to an intitutional actionai, but is not authorized to performai, neither the
“counts as” relation will hold, nor the effects ofai will take place.
– When an action is authorized and is not prohibited, it ispermitted. Usually in the agent literature authorization is not distinguished from permission or the former encompasses the latter. Coherently with the concept of institu- tionalized power [18], we distinguish between the notions of authorization and permission. The main difference between authorization and permission resides in the effects of the action. Whereas the former represents a neces- sary condition for the execution of institutional action, permission reflects the need to regulate the performance of authorized actions, but cannot pre- vent the effects deriving from the performance of a forbidden act.
– An action isprohibited when a norm has created a commitment not to per- form it. If an agent is prohibited to perform actionaibut performs it anyway, the effects of the action take place and the commitment to not perform the action is violated. At this point it is up to the system to impose sanctions to the misbehaving agent, and possibly recover the system to a safe state.
– Obligations are represented by commitments, created by norms, to perform an action of a given type. It may happen that agents do not perform obliga- tory actions; in such a case the commitment becomes violated and the system does not evolve to the expected new state. The violation of an obligation may therefore be punished, and in critical cases the system may be recovered to a safe state by performing a suitable set of actions.
The treatment of sanctions, either direct (fine, expulsion) or indirect (trust, reputation), and the study of plans to recover the system from unsafe states are a wide and interesting research problem we plan to tackle in the future.
5 Conclusions and Future Works
In this paper we have described in short our operational model of Artificial Institutions that can be used for the specification of open interaction systems.
In particular, we have focused on the definition of a standard syntax and an intuitive semantics of the concepts that an agent, or its designer, has to take into account and to reason on, in order to be able to interact properly with different systems.
Existing proposals for the definition of electronic institutions like the one proposed in the EIDE platform [10, 9], the one presented by Cliffe and Padget [3], or the OMNI framework [33] are mainly focused on the specification of the normative component. Unlike them, our model includes also the concepts for defining the institutional reality of the system. Moreover, differently from [10, 9], where the semantics of the communicative acts is given in terms of predefined state transitions, in our model it is possible, using commitments, to define an application independent semantics of a Communicative Act Library, as presented in [14], with a syntax compatible with FIPA-ACL [15].
As far as the formalization of normative aspects is concerned, likewise the other mentioned proposals, we distinguish among permission, obligation, and prohibition. We also distinguish between normative aspects and facts dealing with institutional power [18], which separate meaningful/empowered actions from meaningless actions that do not have an effect. In our opinion, this last type of fact, like in [1], should be considered as part of the declarative apparatus of an Electronic Institution, and not of the normative one. Indeed we think that norms regulate agent interaction by indicating, among all meaningful actions at a certain stage, those that are obliged or forbidden. Moreover an interesting aspect of our proposal is its uniformity; in fact, our operational formalization of norms uses the same concepts used for the definition of the semantics of ACL, that is, social commitments.
Several research questions are still open, and will be tackled in future works.
We will investigate the development of methods for discovering inconsistencies among the specification of one or more artificial institutions. In particular, we are interested in verifying during the specification phase whether certain norms may create obligations to perform unauthorized actions, or under what conditions two norms may generate conflicting commitments. Moreover we intend to devise an explicit representation of the sanctions and repair procedures connected to the violation of commitments.
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Agent Communcation and Institutional Reality N. Fornara, F. Viganò, M. Colombetti
2004
Technical report No. 2
An Operational Approach to Norms in Artificial Institutions F. Viganò, N. Fornara, and M. Colombetti
2005
Technical report No. 3
FIEVeL, a language for the specification and verification of artificial institutions
F. Viganò, 2006
Institute for Communication Technologies
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